The missing data plot shows that Episodes and Seasons have the highest missing rates, affecting over 87% of the dataset, followed by OriginalContent, RuntimeMinutes, and AvgRating at around 65%. These missing values are largely tied to content released between 2021 and early 2022, indicating a failure in metadata ingestion or inconsistencies during that upload period. This data gap significantly limits accurate analysis of series-type content and overall viewer engagement trends. For investors, this represents a blind spot in assessing content value and portfolio performance during a critical growth window.

Viewer engagement significantly differs between original and licensed content, with original content currently underperforming and potentially not resonating well with the audience, while licensed content, likely due to recognizable titles, drives more consistent watch times. The substantial 65% "NA" entries for content type suggest widespread missing labels, hindering accurate classification and weakening insights critical for effective content strategy decisions. This indicates an urgent need for comprehensive content categorization to enhance analytical capabilities and optimize content investment.

XMdeia Company faces significant customer churn, driven by early subscription cancellations, low watch duration, and substantial missing content metadata hindering viewer engagement and content discovery. Underperformance of original content compared to licensed material, coupled with the promotion of low-engagement genres and churn associated with specific subscription plans and seasonal trends, indicates a systemic issue. These factors collectively suggest that poor content targeting and a lack of personalization are the primary drivers of customer attrition.

Geographically Weighted Regression (GWR)

just a test

Google Report

Balancing Innovation and Ethics